RSVP and connect to the growing cybersecurity ecosystem at Georgia Tech that includes:

• Research opportunities with interdisciplinary teams
• Visiting guests coming to GT this semester
• Hacking competitions and clubs
• Resources for entrepreneurial faculty and students
   

Looking for a research or start-up partner? Don't miss it!

Have a research idea? Get feedback from others.

Need to network for your future? Meet experienced professionals and cyber faculty who have advice.

You never know who might add expertise to one of your projects this year!!!

Hosted by the Institute for Information Security & Privacy

RSVP

"I made the very model, but the model was too general: Modeling every cyber vegetable, animal, and mineral."

The Sandia Emulytics capability aims to model all domains of the cyber and cyber-physical landscape, at scale, in order to better understand cybersecurity threats against government networks and critical infrastructure. Whereas physical testbeds are costly to maintain and scale, and simulators fail to represent cyber misbehavior adequately, Sandia Emulytics blends Virtual Machine based testbeds, hardware in the loop, and simulators as needed to maximize fidelity and scale. Now a 10-year program, Sandia Emulytics supports heterogeneous modeling of IT, electric power, telephony, IoT, cyber-physical phenomena, and user behavior, and scales to millions of endpoints. The core toolset is open source and publicly available. This talk will cover the capability today, how attempting to model everything is a necessary but ultimately lost endeavor, and current and future research challenges.
 
David Jakob Fritz, Ph.D., is a principle member of the technical staff at Sandia National Laboratories in Albuquerque, NM. He graduated with a Ph.D. in electrical engineering in 2012 and has been working at Sandia since 2010. He currently leads Sandia's Emulytics program, which aims to advance the state of the art in experimental cybersecurity through large-scale network and cyber-physical emulation. Most recently, he helped expand Emulytics capabilities for IoT and automated threat modeling.
 

The weekly series, sponsored jointly by the Institute for Data & High Performance Computing (IDH), Institute for Materials (IMaT) and Center for Data Analytics (CDA), will continue on most Thursdays during the Fall and Spring Semesters and feature a mix of topics, including those related to big data for materials and manufacturing, as well as other topics critical to the broader area of big data.

The next event will be a special afternoon Workshop on Big Data and Materials on November 7 from 1 to 5 p.m. at the Georgia Tech Hotel.  

The regular "chalk and talk" brown bag lunch series will resume on November 14, with OIT's Chief Technology Officer Ron Hutchins discussing the new HPC building. This event will be held in MiRC 102 A&B. 

Watch a video recording of this event on the IDH website.

All meetings are held on Thursdays during lunchtime. 

Date: November 14
Topic: Big Data and New HPC Building
Presenters(s): Ronald Hutchins

All meetings are held on Thursdays during lunchtime. 

Date: November 21
Topic: Nonlinear Dimension Reduction and Microstructure Space

Abstract: In this talk I will survey some recent advances in nonlinear dimension reduction and manifold learning, especially how can one move beyond PCA to incorporate nonlinearity in reduced dimension representation of microstructures.

Presenters(s): Hongyuan Zha

All meetings are held on Thursdays during lunchtime. 

Date: December 5
Topic: “Using Structure to Solve Underdetermined Systems of linear Equations and Over-determined Systems of Quadratic Equations”
Presenters(s): Justin Romberg

Abstract

We will start by giving a high-level overview of the fundamental results in the field that has come to be known as compressive sensing. The central theme of this body of work is that underdetermined systems of linear equations can be meaningfully “inverted” if they have structured solutions. Two examples of structure would be if the unknown entity is a vector, which is sparse (has only a few “active” entries), or if it is a matrix, which is low rank. We discuss some of the applications of this theory in signal processing and machine learning.

In the second part of the talk, we will show how some of these structured recovery results give us new insights into solving systems of quadratic and bilinear equations. In particular, we will show how recasting classical problems like channel separation and blind deconvolution as a structured matrix factorization gives us new insight into how to solve them.

Bio

Justin Romberg is an associate professor in the School of Electrical and Computer Engineering. He received B.S.E.E. (1997), M.S. (1999) and Ph.D. (2004) degrees from Rice University in Houston, Texas. From Fall 2003 until Fall 2006, he was a postdoctoral scholar in Applied and Computational Mathematics at the California Institute of Technology. In the fall of 2006, Romberg joined the ECE faculty at Georgia Tech. In 2009, he received a PECASE award and a Packard Fellowship, and in 2010, he was named a Rice University Outstanding Young Engineering Alumnus. Romberg is currently on the editorial board for the SIAM Journal on Imaging Science.

All meetings are held on Thursdays during lunchtime. 

Date: January 9
Topic: “Quantification and Low Dimensional Representation of Material Internal Structure Using Spatial Correlations”
Presenters(s): Surya R. Kalidindi
Abstract:
Almost all materials that relate to advanced technologies exhibit a richness of hierarchical internal structures at multiple length scales (spanning from atomic to macroscale). Certain salient features of this structure control the performance characteristics of interest for a selected application. Although there is often some intuition about what these salient features might be, validated protocols do not yet exist for reliably identifying these features. Further, efficient computational protocols do not yet exist for tracking their evolution during the various unit processing/synthesis steps employed in the industrial manufacture of new products/devices. In fact, the optimization of the material structure resulting in improved performance of engineering components is often the main motivation behind all activities in the field of materials science and engineering. Despite its important role, a unified computational framework for the quantification of the material hierarchical structure does not exist currently.  In this talk, I will describe a rigorous theoretical framework developed by my research group for the stochastic quantification of the material structure at any selected length scale, utilizing spatial correlations as the central metrics. This framework combines the use of n-point spatial correlations (or n-point statistics) and principal component analyses to arrive at objective, low-dimensional, representations of material internal structure in establishing core materials knowledge systems.  
Bio:
After earning a Ph.D. in mechanical engineering from the Massachusetts Institute of Technology in 1992, Surya R. Kalidindi joined the Department of Materials Science and Engineering at Drexel University. In 2013, his research group moved to the George W. Woodruff School at the Georgia Institute of Technology, where he has courtesy appointments in the School of Materials Science and Engineering and in the School of Computational Science and Engineering. Kalidindi’s research efforts over the past two decades have made seminal contributions to the fields of crystal plasticity and microstructure design. His current research is directed at developing and validating new data science enabled workflows for the successful realization of accelerated and cost-effective development of enhanced performance materials for advanced technologies.

All meetings are held on Thursdays during lunchtime. 

Date: January 16
Topic: “Scalable, Interactive, and Comprehensible Tools for Data Analytics”
Presenters(s): Polo Chau

Abstract:

Massive datasets now arise in virtually all domains. Yet, making sense of these data remains a fundamental challenge. At the “Polo Club of Data Science,” we are innovating at the intersection of data mining and human-computer interaction (HCI) to combine the best from both worlds to create scalable, interactive tools for making sense of graphs with billions of nodes and edges.

I will briefly describe some of our latest work, both on-going and published, that aims to tame big data through scalable algorithms, interactive visualization, and comprehensible models (machine learning/data mining) that users can more easily understand and work with.

Bio:

Duen Horng (Polo) Chau is an assistant professor in Georgia Tech’s School of Computational Science and Engineering and an adjunct assistant professor in the School of Interactive Computing. Polo received his Ph.D. from the Machine Learning Department at Carnegie Mellon University (CMU) and his Master’s degree in Human-Computer Interaction (HCI) from CMU.

Chau solves large-scale, “real world” problems that impact society. His NetProbe auction fraud detection system was featured in The Wall Street Journal and on CNN. His patented Polonium malware detection technology (with Symantec) protects 120 million people worldwide.

Chau’s thesis work received an honorable mention in Carnegie Mellon's School of Computer Science Distinguished Dissertation Award competition. He is the only two-time Symantec fellow, and he received a Yahoo! Key Scientific Challenges Award. Chau contributes to the PEGASUS peta-scale graph mining collaboration, which won an Open Source Software World Challenge Silver Award. He is also an award-winning designer and created Carnegie Mellon’s most recently used ID card design.

All meetings are held on Thursdays during lunchtime. 

Date: January 23
Topic: "Interactive Visual Analytics for Text Data Analysis"
Presenter: Haesun Park

Abstract:

Many modern data sets can be represented in high dimensional vector spaces and have benefited from computational methods that utilize advanced techniques from numerical linear algebra and optimization. Visual analytics approaches have contributed greatly to data understanding and analysis due to utilization of both automated algorithms and human’s quick visual perception and interaction. However, visual analytics targeting high dimensional large-scale data such as a document collection has been challenging due to low dimensional screen space with limited pixels to represent data.

We present some of the key foundational methods for supervised dimension reduction such as linear discriminant analysis (LDA), dimension reduction and clustering/topic discovery by nonnegative matrix factorization (NMF), and visual spatial alignment for effective fusion and comparisons by orthogonal Procrustes. We demonstrate how these methods can effectively support interactive visual analytic tasks that involve large-scale document data sets in two of the visual analytics systems, UTOPIAN for interactive topic discovery and VisIRR for visual document retrieval and recommendation.

Bio:

Prior to joining the College of Computing's School of Computational Science and Engineering faculty in 2005, Haesun Park was on the faculty at the University of Minnesota, Twin Cities, from 1987 to 2005, and from 2003 to 2005, she also served as a program director for the Computing and Communication Foundations Division at the National Science Foundation in Arlington, Va. She is the director of the NSF/DHS Foundations of Data and Visual Analytics (FODAVA-Lead) initiative and executive director of the Center for Data Analytics (CDA) at Georgia Tech.

Park's current research interests include numerical algorithms, pattern recognition, bioinformatics, information retrieval, and data mining. She has published more than 100 research papers in these areas and has served on numerous conference committees and journal editorial boards. Currently, she is on the editorial board of BIT Numerical Mathematics, SIAM Journal on Matrix Analysis and Applications, and the International Journal of Bioinformatics Research and Applications. In 2008 and 2009, Park served as a conference co-chair for the SIAM International Conference on Data Mining, and in 2013, she was elected as a SIAM Fellow.

All meetings are held on Thursdays during lunchtime. 

Date: February 6
Topic: "Understanding Language Variation in Social Media"
Presenter: Jacob Eisenstein

Abstract:

An increasing amount of informal communication is conducted in written form, through computer-mediated channels such as social media. This offers new challenges and opportunities for large-scale text analysis. I argue that social media analytics should be guided by an understanding of how social media language differs from other written language, and why. I will describe a series of studies that document language variation across a number of different social variables. In some cases, social media writing tracks spoken language variation; in other cases, relatively novel "netspeak" terms like emoticons and abbreviations can also be strongly correlated with demographics and geography. Our recent work concerns language change over time, using a new dataset of hundreds of thousands of authors over nearly three years. Aggregating across thousands of words, we build a unified model of the geographic and demographic factors that drive the spread of words between cities.

This research is in collaboration with David Bamman, Brendan O'Connor, Tyler Schnoebelen, Noah A. Smith, Eric P. Xing, and Yi Yang.

Bio:

Jacob Eisenstein is an assistant professor in the School of Interactive Computing at Georgia Tech. He works on statistical natural language processing, focusing on social media analysis, discourse, and latent variable models. Eisenstein was a postdoctoral researcher at Carnegie Mellon and the University of Illinois. He completed his Ph.D. at MIT in 2008, winning the George M. Sprowls dissertation award.

All meetings are held on Thursdays during lunchtime. 

Date: February 20
Topic: “Predictive Analytics for Improving the Reliability and Sustainability of Engineering Systems”
Presenter: Nagi Gebraeel

Abstract: 

Many high-valued engineering assets used in the manufacturing and service sectors are today being monitored by hundreds and perhaps thousands of sensors. Typically, the goal is to monitor system performance and degradation for numerous purposes, one of which is the prevention of unexpected failures. This talk focuses on how to effectively utilize sensor data to predict future system degradation and remaining lifetime (aka. prognostics).

The talk will begin by introducing a basic prognostic framework and how it has been implemented (through a live streaming demo, if possible). Next, the talk will focus on some scalability challenges that arise once we start dealing with big (sensor) data, which will be followed by a moderately technical discussion about some of the recently developed state-of-the-art modeling techniques that have targeted a few facets of this problem. 

Bio:

Nagi Gebraeel is the Chandler Family Associate Professor in the School of Industrial and Systems Engineering at Georgia Tech. He received his M.S. and Ph.D. degrees in industrial engineering from Purdue University in 1998 and 2003, respectively. Gebraeel’s research interests focus on leveraging condition-based sensor data streams to improve the predictability of unexpected failures of engineering systems and on improving subsequent operational and logistical decision making processes. He is a member of the Institute of Operations Research and Management Science (INFORMS), the Institute of Industrial Engineers (IIE), and the American Institute of Aeronautics and Astronautics (AIAA).

All meetings are held on Thursdays during lunchtime. 

Date: February 27
Topic: “Time Series Data in Healthcare: From Mental Health to the ICU”
Presenter: Gari Clifford

Abstract:

The enormous volume of available data from patients in both the hospital and outpatient settings presents both exciting opportunities for healthcare and several key problems. These include:

1. Traditional time series analysis algorithms are tuned to be over-sensitive, which results in many false alarms, and the expectation that an expert will over-read each alarm. With patient-to-doctor ratios ranging from 100 to 50,000 to one, this paradigm will no longer address the issues.
2. Multiple sensors can record similar information, and so we must build trust metrics to identify the signals we can trust, or work out ways to combine the signals together in a robust manner.
3. Humans disagree on diagnoses and labels, even when the disease is well described. Inter- and intra-human bias and variance in diagnoses must be addressed, particularly if we are to build automated algorithms from the labeled data.
4. Data labeling of medical data is vast and most likely impossible to do so by hand. Low-cost, semi-supervised and unsupervised approaches to event labeling, state definition, and feature extraction are needed. Finding clinically acceptable approaches to address this problem may be key to developing appropriate predictive machine learning algorithms.

Bio:

Gari Clifford recently joined the Emory and Georgia Tech faculties as an associate professor of bioinformatics and biomedical engineering. Previously, he was an associate professor of biomedical engineering at Oxford University and the director of the Centre for Doctoral Training in Healthcare Innovation at Oxford’s Institute of Biomedical Engineering.

Clifford’s research group explores machine learning and signal processing to extract actionable information from medical data. In particular, the lab focuses on intensive care medicine, cardiovascular disease, circadian rhythm disorders, sleep, and mental health. This research is aligned with the concept of sustainable healthcare, and he has a particular interest in mHealth in resource-constrained settings and circadian rhythms.

Prior to joining the faculty at Oxford, Clifford was a principal research scientist at MIT, where he spent six years managing the engineering effort behind a multi-million dollar project to collect and analyze the world's largest public database of hospital data. Clifford also serves on the international advisory and editorial boards of several organizations, including the NIH Public Access Resource, PhysioNet, and the Institute of Physics' Journal of Physiological Measurement.

In addition to licensing several patents, Clifford has been closely involved in the regulatory approval of medical devices for more than ten years. Also, he has received several awards for his research, including the 2009 Martin Black Prize, the 2010 mHealth Alliance Award, the 2011 International Engineering World Health Design Competition, the Dell Best Innovation Leveraging Technology Award in 2012, and the Computing in Cardiology Challenges in 2008, 2012, and 2013 for ECG analysis and mortality prediction.

Dr. Justin Romberg

Associate Professor, School of Electrical and Computer Engineering,Georgia Institute of Technology

Title:

Using structure to solve underdetermined systems of linea

Abstract:

We will start by giving a high-level overview of the fundamental results in the field that has come to be known as compressive sensing.  The central theme of this body of work is that underdetermined systems of linear equations can be meaningfully "inverted" if they have structured solutions.  Two examples of structure would be if the unknown entity is a vector which is sparse (has only a few "active" entries) or if it is a matrix which is low rank.  We discuss some of the applications of this theory in signal processing and machine learning. 

In the second part of the talk, we will show how some of these structured recovery results give us new insights into solving systems of quadratic and bilinear equations.  In particular, we will show how recasting classical problems like channel separation and blind deconvolution as a structured matrix factorization gives us new insight into how to solve them.

Bio:

Dr. Justin Romberg is an Associate Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology.  Dr. Romberg received the B.S.E.E. (1997), M.S. (1999) and Ph.D. (2004) degrees from Rice University in Houston, Texas.  From Fall 2003 until Fall 2006, he was a Postdoctoral Scholar in Applied and Computational Mathematics at the California Institute of Technology.  In the Fall of 2006, he joined the Georgia Tech ECE faculty.  In 2009 he received a PECASE award and a Packard Fellowship, and in 2010 he was named a Rice University Outstanding Young Engineering Alumnus.  He is currently on the editorial board for the SIAM Journal on Imaging Science.

Title: Biodiversity Informatics: Using Information Technology to face the challenges of Biodiversity Conservation

Abstract:
Biodiversity conservation involves a deep scientific understanding of biodiversity at the genetic, species, and ecosystem level. However there are huge information gaps for scientists and decision makers to do their work. In many cases, enough high quality up to date information has not been generated, in others, relevant information is scattered, locked away or stored in non-standard formats. As scientists started putting together this puzzle at each of the three levels of biodiversity and establishing connections across levels, it has become evident that information technologies play a critical role.

Biodiversity conservation poses challenges not just at the scientific knowledge generation and management level. It is also challenging in terms of helping find sustainable uses and support concrete biodiversity conservation actions in the field.

How ITs support these biodiversity conservation challenges is the focus of this introductory talk about Biodiversity Informatics. In addition to presenting the current state of the art, we will discuss some of the topics presented in the recently issued GBIO (Global Biodiversity Informatics Outlook) document, which ”proposes a framework that will help harness the immense power of information technology and an open data culture, to gather unprecedented evidence about biodiversity and to inform better decisions.”

Bio:
Dr. Erick Mata is an associate professor of Computer Science and the director of graduate studies at the Costa Rica Institute of Technology. His research interests include biodiversity informatics, scientific visualization, algorithmic graph theory, and multimedia systems.

Dr. Mata obtained his Ph.D. in computer science at the University of Oregon in 1990. He was the Director of Biodiversity Informatics at INBio, the National Biodiversity Institute of Costa Rica, for 15 years from 1995 to 2010. From 2011 through 2013 he was the Executive Director of the Encyclopedia of Life (EOL), a global initiative lead by the Smithsonian Institution that has generated more than 800,000 species pages and integrates information from more than 280 partners worldwide, including more than 2.3 million images and 40 million pages of scientific publications.

Dr. Mata served as chair of the Global Biodiversity Information Facility (GBIF) Outreach and Capacity Building Subcommittee (2001-2005) and as chair of the GBIF Science Committee (2007-2009). He was the Coordinator of the Inter-American Biodiversity Information Network (IABIN) Species and Specimen Thematic Network from 2006 to 2010.

Title: The Aha! Moment: From Data to Insight

Abstract:
The amount of data in the world is increasing at incredible rates. Large-scale data has potential to transform almost every aspect of our world, from science to business; for this potential to be realized, we must turn data into insight. In this talk, I will describe two of my efforts to address this problem computationally.

The first project, Metro Maps of Information, aims to help people understand the underlying structure of complex topics, such as news stories or research areas. Metro Maps are structured summaries that can help us understand the information landscape, connect the dots between pieces of information, and uncover the big picture.

The second project proposes a framework for automatic discovery of insightful connections in data. In particular, we focus on identifying gaps in medical knowledge: our system recommends directions of research that are both novel and promising.

I will formulate both problems mathematically and provide efficient, scalable methods for solving them. User studies on real-world datasets demonstrate that our methods help users acquire insight efficiently across multiple domains.

Bio:
Dafna Shahaf is a postdoctoral fellow at Stanford University. She received her Ph.D. from Carnegie Mellon University; prior to that, she earned an M.S. from the University of Illinois at Urbana-Champaign and a B.Sc. from Tel-Aviv University. Shahaf's research focuses on helping people make sense of massive amounts of data. She has won a best research paper award at KDD 2010, a Microsoft Research Fellowship, a Siebel Scholarship, and a Magic Grant for innovative ideas.

Currently, industry leaders devote large-scale efforts on developing ways to derive value from these data and on designing new technologies that enable its exploitation, while Georgia Tech is a recognized innovator and developer of both big data technologies and its applications.

The Big Data Industry Forum brings together leaders from industry and Georgia Tech’s big data researchers to discuss the vision for big data, the value and opportunities it provides to industries, and the challenges that lie ahead to fully take advantage of the vast amounts of data being produced today.

The forum includes keynote talks by industry leaders, as well as provocative panel discussions, and also showcases research projects and new technologies being developed at Georgia Tech today.

For a detailed agenda of the event, please download a PDF version or visit the Big Data Industry Forum webpage.

Register Now

All meetings are held on Thursdays during lunchtime. 

Date: March 6
Topic: TBA
Presenter: TBA

All meetings are held on Thursdays during lunchtime. 

Date: March 13
Topic: TBA
Presenter: TBA

All meetings are held on Thursdays during lunchtime. 

Date: March 20
Topic: TBA
Presenter: TBA

“Lightning Talks” Format:
* Five minutes to present your current interest
* Discuss a problem, a solution, or “anything” interesting related to big data and materials
* No questions will be taken at the end
* Speakers will be called to participate in the order their registrations are received

To participate in the “lightning talks,” please complete our Doodle poll. 

This bi-weekly brown bag series, brought to you by the FLAMEL Traineeship Program, focuses on topics in the areas of data and materials. The series will begin with talks by faculty who are supervising FLAMEL students, and will then progress to talks by FLAMEL students themselves as they present on their projects. 

Please bring a “brown bag” lunch and drink.

Lunch and drinks provided courtesy of the Institute for Materials (IMAT).

Abstract

By virtue of natural selection through competition for limited resources, biological structures require an extreme economy of materials while still providing a robust tolerance to the defects that develop as a matter of course through growth and maturation. Evolutionary refinement has produced myriad structures with properties superior to those of manmade materials, properties contingent upon complex interactions between different levels of structural hierarchy. Through the application of natural design principles and versatile, growth-like additive manufacturing techniques such as 3D printing, we are poised to reimagine the standards of materials research and sustainable manufacturing. While nature provides a wealth of design opportunity, the sheer volume of possibilities presents an imposing hurdle; the need for efficient methods of down-selection is clear. Currently, finding an appropriate natural hierarchy requires extensive literature review and analysis; for bio-inspired design to become more amenable to engineers in general, there needs to be a better interface for structural investigations. We endeavored to develop a general approach to bio-inspired materials design research, and, moreover, to develop the groundwork for a database that would facilitate such research. The objective of this talk is to present the proposed data structure for the storage and comparison of hierarchical structures, and discuss computational approaches that can simplify the process of choosing appropriate structures for focused investigation.

Bio

Jeannette Yen is the director of Georgia Tech’s Center for Biologically Inspired Design (CBID). The goal of CBID is to facilitate, develop infrastructure for, and promote interdisciplinary research and education. Science and technology are increasingly hitting the limits of approaches based on traditional disciplines, and Biology may serve as an untapped resource for design methodology, with concept-testing having occurred over millions of years of evolution. Experiencing the benefits of Nature as a source of innovative and inspiring principles encourages us to preserve and protect the natural world rather than simply to harvest its products.

Jeannette Yen’s Ph.D. is in biological oceanography where she studies how fluid mechanical and chemical cues transported at low Re flow serve as communication channels for aquatic organisms, primarily plankton: the base of aquatic food webs.

Abstract

The talk will be focused on methods for predicting the nucleation of defects in atomistic simulations. The prediction of instabilities in the context of atomistic and homogenized atomistic systems shall be discussed. First, we develop an iterative, linear-scaling framework based on the Lanczos algorithm for determining the onset and mode of instability in atomistic systems. We utilize the proposed formulation to demonstrate that during nanoindentation induced dislocation nucleation, the trajectories of atoms through configurational space are significantly more complicated than those associated with pure slip. Further, through an example of hydrostatically triggered cavitation, we establish that localizing the stability analysis and employing cutoffs for the interatomic potential can both lead to spurious instabilities. Next, based on the Legendre-Hadamard condition, we develop a variant of the conjugate gradient method for predicting defect nucleation in homogenized atomistic systems. We utilize the proposed approach to determine the ideal strength of Aluminum when subject to uniaxial and hydrostatic stresses. In particular, we demonstrate that defects do not nucleate even in the presence of extremely large compressive hydrostatic stresses. Additionally, we show that smaller stresses are required for homogeneous dislocation nucleation in uniaxial compression compared to uniaxial and  hydrostatic tension.

Bio

Pradeep is a second year PhD student in the department of Civil & Environmental engineering at Georgia Tech, specializing in the area of Mechanics & Materials. He is advised by Prof. Phanish Suryanarayana and is currently working on developing a linear scaling code for electronic structure calculations using Kohn-Sham Density Functional Theory. The work aims to develop the code for massively parallel architectures in order to study large systems of atoms at extreme conditions. Pradeep got his Bachelor's degree from Indian Institute of Technology Madras and has a Masters from The University of Texas at Austin.

Lunch and drinks provided courtesy of the Institute for Materials (IMAT).

In addition to those already involved in the FLAMEL program, faculty and students interested in becoming more involved in FLAMEL are especially encouraged to attend. 

Please register for the event online.

Agenda

9:00–9:15          FLAMEL Overview
                          Dr. Richard Fujimoto

9:15–9:45          Experimental Design as an Organizing Principle for Materials Design
                          Dr. Martha Grover, ChBE & Dr. JC Lu, ISyE

9:45– 10:15       Flexible Polymeric Devices: Towards Predicting Device Performance from
                          Morphological Data
                          Dr. Elsa Reichmanis & Dr. Martha Grover, ChBE

10:15–10:45     Processing-Microstructure Relation
                         Dr. Hamid Garmestani, MSE

10:45–11:00     Break 

11:00–11:10     How to Quantify a Bowl of Spaghetti: Predicting Macro-scale Electronic
                         Properties in Thin Films of Conjugated Polymers
                         Nils Persson

11:10–11:20     Developing Structure-Property Linkages for Glass-Fibre Reinforced
                         Composites
                         Alicia White

11:20–11:30     Computational Approaches to Identify Multi-layer Formation and Growth on
                         Tungsten Nanowires
                         Jason Allen

11:30–11:40     Material Informatics for X-rays Scattering Data
                         David Brough

11:40–11:50     Crystallinity Analysis in Polymer Molecular Dynamics Simulations
                         Alex Lohse

11:50–1:00       Luncheon      

1:00–1:30         Data Science and Cyber-Infrastructure Enabled Integrated Workflows to
                         Accelerated and Cost-Effective Advanced Materials Development
                         Dr. Surya Kalidindi, ME

1:30–2:00         The Digital Backbone of the Materials Informatics Course
                         Dr. Tony Fast, ME

2:00–2:30         Large-scale High-performance Parallel Quantum Chemistry
                         Dr. Edmond Chow, CSE

2:30–2:45         Break 

2:45–3:00         Interactive Graph Visualization, Exploration, and Sensemaking
                         Dr. Polo Chau, CSE

3:00–3:15        Thermal Transport at the Interfaces of Nanomaterials
                        Dr. Satish Kumar, ME

3:15–3:30        Materials Problems in Manufacturing Process Modeling and Simulation: A Role 
                        for Data Science-based Approach
                        Dr. Shreyes Melkote, ME

Date:               Thursday, March 26, 2015

Location:         Pettit/MiRC Building, Room 102 A&B

Time:               11:00am – 12:00pm

Title: 

Microstructure and Processing Design for Photovoltaic Applications

Abstract:

The possibility for a program of computational modeling, processing and characterization will be explored to improve the property of the multi-crystalline cast silicon materials for photo-voltaics applications.  A direct linkage between the evolution of the microstructure and the process parameters is not presently available in the silicon technology and will be explored. The modeling methodologies and the consequent computer programs will provide manufacturers an essential tool to optimize the process parameters to produce a more cost efficient final product during casting of Si for solar cell applications.

Bio:

Jason Allen is a first year Ph.D. student in the School of Materials Science and Engineering. He received a B.S. degree in physics from Southern Polytechnic State University in 2002 and a B.S. degree in materials science and engineering from Georgia Tech in 2013.  Currently, Jason is working under the advisory of Dr. Hamid Garmestani and is using data science and computational approaches to identify process-structure linkages for silicon in use in photovoltaic applications.

Lunch and drinks provided courtesy of the Institute for Materials (IMAT).

Lunch and drinks provided courtesy of the Institute for Materials (IMAT).

Lunch and drinks provided courtesy of the Institute for Materials (IMAT).

 Title:

 Collaboration and Information Sharing for the New Age of Materials Research

Abstract:

Advanced experimental techniques for creating new materials have created a surge in materials data over the past several decades. One goal of the Materials Genome Initiative is to develop an infrastructure to utilize that data in accelerating materials development. Past engineering and science golden ages, such as the Scientific and Industrial Revolution periods, have been initiated by an invention from which numerous innovations resulted. Today, the Information Revolution will require the same inventiveness. New tools and methods for collaboration and data management are paramount to realizing the ideals of the Materials Genome Initiative. The talk will present historical perspectives on collaboration and information sharing, evaluate some current tools available, and discuss potential future tools needed.

Bio:

Alex Lohse is in his first year of the Ph.D. program in the School of Materials Science and Engineering (MSE) at Georgia Tech, after recently graduating with a B.S. in MSE from Purdue University. During his time at Purdue, he worked for GE-Aviation on a variety of military and commercial jet engine material systems; for Northrop Grumman on microelectronics technology for satellites; and performing research in sustainable metal processing. He also played the “Big Bass Drum” in Purdue’s All-American Marching Band. In his spare time he loves to travel, play soccer, is an avid runner, and will do just about anything outdoors including hiking, kayaking, and cycling.

Lunch and drinks provided courtesy of the Institute for Materials (IMAT).

PyMKS - Materials Knowledge Systems in Python

Abstract:
Community development of materials data analytics toolsets can dramatically alter the landscape of the existing materials innovation ecosystem, and transform the vision outlined in the MGI and ICME documents into reality. The Materials Knowledge Systems framework provides a viable approach for efficient exploration of the unimaginably large materials and process (i.e. manufacturing) design space through the development and implementation of efficient meta-models. Materials Knowledge Systems in Python (PyMKS) aims to seed and nurture an emergent materials analytics user group focused on homogenization and localization linkages central to virtually all multiscale materials modeling efforts. PyMKS provides high level access to the Materials Knowledge Systems framework through simple APIs and leverages open source scientific computing and machine learning packages in Python. An overview of the PyMKS project as well as examples using this Materials Informatics tool will be presented.

Bio:
David Brough is a third-year PhD student in the School of Computational Science and Engineering. As an undergraduate, David studied theoretical physics and researched the evolution of chaotic systems using neural networks at Westminster College. He also earned a Master’s degree in experimental condensed matter physics at Brigham Young University where he fabricated and characterized thin-films used in nanostructured high capacity battery electrodes and in X-ray windows. David’s current research interest is creating materials informatics tools and protocols that efficiently leverage large datasets to learn structure-processing and structure-property relationships.

Lunch and drinks provided courtesy of the Institute for Materials (IMAT).

Abstract:  Highly productive cross-disciplinary collaborations cutting across materials science, manufacturing, product design, computational sciences, and data sciences are critically needed for the success of the emerging national strategic initiatives such as the Materials Genome Initiative (MGI) focused on the accelerated development of new/improved advanced materials and their deployment in emerging technologies. In response to these critical national needs, and with the guidance and support of GT’s IMAT (Institute for Materials) and FLAMEL (NSF funded IGERT), we have initiated the development of a Github based e-collaboration platform, whose primary purpose is to facilitate intimate exchange of ideas, data, codes, knowledge, and expertise between potential cross-disciplinary team members engaged in a diverse range of materials innovation efforts at GT. Called MATIN, this e-collaboration platform is aimed at nucleating an emergent community that is particularly adept at injecting customized materials data science and informatics tools into the ongoing materials innovation endeavors at GT in an effort to dramatically enhance their productivity. We will present the current status of this effort and discuss future plans. We are specifically seeking individuals interested in taking on leadership roles in the design, development, and launch of this e-collaboration platform for the entire GT materials research community.

Announcing the 3rd annual SouthEast Regional Symposium (SERES III)

This for-students, by-students conference will engage minds from all disciplines in research and ideas for the future of  sustainability, energy materials, technology, policy, and business.

Register today to compete for prizes! http://nesac.gatech.edu/

Who:

Students from all parts of campus, and from across the region

What:

Research conference and competition

When:

Wednesday, May 6

Where:

IBB Atrium & Room 1128

Showcase your ideas,

Apply that class project you’ve been working on,

Gain presentation experience,

Discover new perspectives,

Engage with interdisciplinary speakers

Register for free!

Submit a brief poster abstract

by March 20 to enter the competition and you could win an iPad!

http://nesac.gatech.edu/

Date:              Thursday, August 27, 2015

Location:        Klaus 1116 East
Time:              11:00am – 12:00pm

The Institute for Leadership and Entrepreneurship (ILE), is an interdisciplinary institute that encourages values-based leadership and socially responsible entrepreneurship.  ILE empowers our community to account for the economic, social, and environmental imapcts of business.  Come find out about social entrepreneurship education and the various competitions at Tech (I2S, GSVC, Start-up, TiGer) that promote entrepreneurship, and are open to graduate students.

Lunch and drinks provided courtesy of the Institute for Materials (IMAT).

Bio:

Dori Pap directs the Eastern Europe Study Abroad Program, coordinates the IMPACT Speaker Series, runs the Ideas to Serve student social innovation competition, and teaches courses on social entrepreneurship. She is the faculty lead for the Global Social Venture Competition, a partnership between Georgia Tech and Berkley's Haas School of Business. Dori serves as the faculty advisor for Enterprise to Empower, a Georgia Tech student organization dedicated to educating and empowering students in social enterprise.

Date:  Thursday, September 10, 2015

Location:  Klaus Building, Room 1116 East

Time:  11:00am – 12:00pm

Flashpoint is unique in implementing startup engineering, a business creation and innovation process developed by Dr. Merrick Furst at Georgia Tech. Flashpoint works closely with founders to enable them to think clearly about their businesses. It is unique in implementing startup engineering, a business creation and innovation process developed by Dr. Merrick Furst at Georgia Tech. Its companies have attracted more than 150 MM in commitments from angels and investors, and have a market cap of over 500 MM.

Bio:

Merrick is the founder of Georgia Tech’s Flashpoint, a first-of-its-kind startup engineering studio that develops and produces exceptional technology startup companies.  He is Georgia Institute of Technology’s first “distinguished professor of computing”.  The GT “Threads” program in the College of Computing was his creation, and he is one of the three producers of The InVenture Prize, a live-broadcast tv show that NPR describes as American Idol for Nerds.  Merrick is a co-founder of the internet security firm Damballa and is an early-stage fund investor.  Prior to joining Georgia Tech, Merrick was the founder and CEO of Essential Surfing Gear, an internet software company, which was acquired in 2000.  At the University of California at Berkeley he served as president and director of the International Computer Science Institute, and he established its Center for Internet Research.  Prior to Berkeley, Merrick was a professor and associate dean in the School of Computer Science at Carnegie Mellon University. Merrick is an inventor, recipient of the first Presidential Young Investigator Award in computer science, and early creator electronic post-it notes, which were best-sellers on PCs.

Lunch and drinks provided courtesy of the Institute for Materials (IMAT).

Time:              11am-12pm             
Place:              Klaus Classroom 1447 (Please note that because this has to be held in a classroom, lunch will not be served at this particular talk)               

 Speaker:          Dr. Jeannette Yen, Director, Center for Biologically Inspired Design (CBID)

 Title: 

Biologically Inspired Materials Design: Hierarchical Structures inNature      

Abstract:

Living organisms serve as working prototypes of designs that can inform us of how nature practices an economy of materials. The hierarchical patterns of nature are diverse and fascinating. The question is: how does nature build such structures and can we mimic the methods to “expand” the performance of materials? Hierarchical analyses searches for design principles by comparing how similar functions are achieved by organisms at various scales, in different habitats, or by different lineages. Biologically Inspired Design (BID) is an emerging cross-disciplinary domain, where scientists, engineers and designers combine forces “to study and distill principles and functions found in biological systems that have been developed through evolution” and apply this knowledge “to produce novel and exciting basic technologies and new approaches to solving scientific problems”. This synthetic framework can improve the partnership between nature and humans and infuse sustainability into technology design.

Bio:

Dr. Jeannette Yen is the Director of the Georgia Institute of Technology’s Center for Biologically Inspired Design (CBID). The goals of CBID are to bring together faculty who seek to facilitate interdisciplinary research and education for innovative products and techniques based on biologically-inspired design solutions.  CBID participants believe that science and technology are increasingly hitting the limits of approaches based on traditional disciplines, and Biology may serve as an untapped resource for design methodology.  Experiencing the benefits of Nature as a source of innovative and inspiring principles encourages us to preserve and protect the natural world rather than simply to harvest its products.  Jeannette team-teaches the interdisciplinary course in biologically inspired design [http://www. youtube.com/watch?v=PMlvUJ9_GSk].  She has been a Professor of Biology at Georgia Tech since 2001 with a Ph.D. in the interdisciplinary environmental science of biological oceanography where she studies how fluid mechanical and chemical cues transported at low Re flow serve as communication channels for micro-aquatic organisms, primarily zooplankton: key link in aquatic food webs. She has been to all 7 continents, including Antarctica for her research and education.

The hackathon will be held on Friday, December 11 from 9am to 6pm in the IPST Bldg, room 114 and again on Monday, December 14 from 9am to 4pm in the Marcus Nanotechnology Bldg, room 1117-1118.

Time:              11am-12pm             
Place:              Klaus 1116 East               

Speaker:         Andriy Dotsenko, First-year FLAMEL trainee

Title:

“Development of a Combinatorial High Throughput (CHT) Alloy Synthesis Technique for Additive Manufacturing using Dry Powder Printing and Controlled Laser Melting”

Abstract:This talk describes the development of a combinatorial high throughput (CHT) alloy synthesis technique for Additive Manufacturing (AM) that combines experimental and analytical components tailored to advance the understanding of process-microstructure and microstructure-property relationships. The experimental component includes precision dry powder printing (DPP) for alloy composition control and Controlled Laser Melting (CLM) for consolidation to create a large set of physical alloy samples of unique composition under controlled processing conditions. The analytical component includes quantitative microstructural analysis and material property measurements of the fabricated samples. Together, these components form the basis of a powerful tool for rapid screening of microstructure-property-processing relationships as a function of alloy composition. The DPP and CLM techniques are presented along with a demonstration of the CHT technique on a family of aluminum alloys. The presented technique has the potential to serve as a valuable tool in advanced alloy development for AM as well as for streamlining process parameter optimization.

Bio:

Andriy Dotsenko is a Ph.D. student in the school of Mechanical Engineering, working with Dr. Suman Das in the Direct Digital Manufacturing Lab (DDML). He has a B.S. in Physics from Stony Brook University and industry experience working at HYPRES, inc. in the area of superconducting electronics. His current research is metal Additive Manufacturing (AM) at the intersection of Mechanical Engineering and Materials Science with the goal of developing a light-weight, high-strength aluminum alloy optimized for AM. A general Combinatorial High Throughput (CHT) alloy synthesis technique for alloy development and discovery is developed as a tool to realize this goal, and can be extended to other alloy systems.

Andriy enjoys hiking, music, and social dancing, helping organize the Georgia Tech Salsa Club.

Time:              11am-12pm             
Place:              Klaus 1116 East           

Speaker:         Robert Pienta, First-year FLAMEL trainee

Title:

“Modeling Process-Structure Linkages In Ternary Eutectoid Al-Ag-Cu Alloys”
Abstract:

Process-structure-property (PSP) linkages are critical for furthering the knowledge base of material informatics.  This talk describes our research into modeling the process-structure linkages for both the steady state and transient behavior of ternary eutectoid Al-Ag-Cu alloys. Our objective is to understand how solidifying aluminum alloys' microstructures are determined by the solidification velocity and alloy concentrations. We utilize state-of-the-art simulation results of ternary eutectoid Al alloy solidification (for further detail on the simulation see [1]). The simulations provide a data-rich transient solidification period that--in most cases--arrives at a steady state. In this talk I will present our methods and results for modeling the linkages between the simulated solidification process and the alloy microstructures.  I will also cover the ongoing challenges we have faced, which motivate the need of non-linear dimensionality reduction techniques for modeling transience in materials.

[1]  -  Hötzer, Johannes and Jainta, Marcus and Steinmetz, Philipp and Nestler, Britta and Dennstedt, Anne and Genau, Amber and Bauer, Martin and Köstler, Harald and Rüde, Ulrich (2015) Large scale phase-field simulations of directional ternary eutectic solidification.Acta Materialia (93), pp. 194-204. DOI: 10.1016/j.actamat.2015.03.051. ISSN 1359-6454.

Bio:

Robert Pienta is a PhD student in computational science and engineering at Georgia Tech. As an undergraduate, he attended Rose-Hulman Institute of Technology majoring in computer science and mathematics. His academic interests are human-in-the-loop machine learning, visual analytics, and large-scale data mining. While in FLAMEL he aspires to utilize visualization and data mining techniques to improve the quality of models and material simulations. For fun he paints portraits and runs.

Lunch and drinks provided courtesy of the Institute for Materials (IMAT).

Time:              11am-12pm             
Place:              Klaus 1447             

Speaker:         Alex Lohse, 2^nd year FLAMEL Trainee

Title:  “Molecular Dynamics and Material Informatics”

Abstract:

Molecular dynamics (MD) simulations are a useful way to study the underlying molecular mechanisms that occur when material systems are subjected to some stimuli. Material informatics techniques are well poised to uncover molecular level structure information. In this talk I will briefly discuss molecular dynamics simulations, specifically of polymer and polymer matrix composite systems. A review and some examples will be presented to show different ways informatics techniques have/can be applied to MD.

Bio:

Alex Lohse is in his second year of the Ph.D. program in the School of Materials Science and Engineering (MSE) at Georgia Tech, after graduating with a B.S. in MSE from Purdue University. During his time at Purdue, he worked for GE-Aviation on a variety of military and commercial jet engine material systems; for Northrop Grumman on microelectronics technology for satellites; and performing research in sustainable metal processing. He also played the “Big Bass Drum” in Purdue’s All-American Marching Band and studied abroad in France and China. In his spare time he loves to travel, play soccer, is an avid runner, and will do just about anything outdoors including hiking, kayaking, and cycling.

*Our next Chalk-Talk is scheduled for Thursday, February 11, with discussions led by first year FLAMEL trainee Andriy Dotsenko.  For a list of this semester’s upcoming talks, please visit http://flamel.gatech.edu/newsroom

Time:              11am-12pm             
Place:              Pettit/MiRC, Room 102           

Speaker:         Christopher Shartrand, First-year FLAMEL trainee

Title:

“Structure-Property Relationships in Organic Field-Effect Transistors”

Abstract:

Organic Field-Effect Transistors are a common device used in modern day development of organic electronics. Until recently, most research regarding OFETs has been focused on developing novel process techniques while improvement in the desired property mobility has remained stagnant. The problem now is to develop a statistical methodology that focuses on this fact.

This talk will detail the initial steps in the development of the methodology. It will contain an in-depth discussion on physically justified features for data reduction, an outline of the difficulties of regression modeling in a small response environment, and the possible ways that relevant research outside of our process design can be used to deal with these issues.

Bio:

Chris is a first year PhD student in the School of Industrial and Systems Engineering. He received a B.S. degree in Applied Mathematics from the State University of New York at Fredonia. Before Georgia Tech he had the opportunity to participate in two unique internships and a REU over a diversified field of disciplines. He has worked as a Demographic Data Analyst for Pitney Bowes Corporation and as an Radiological Emergency Planner for the New York State Office of Emergency Management. Additionally during his REU,  he conducted research involving CD4+ T-cells at the Virginia Bioinformatics Institute at Virginia Tech.

Chris is currently involved in research under the advisement of Drs. J-C Lu, Martha Grover, and Elsa Reichmanis. He is attempting to aid in the development of a scientific data-synthesis engine for unifying available big-data embedded in theoretical models, model simulations and past experiments. The process will aid toward designing new experiments that shore up potential knowledge gaps. From there the goal is to create a learning process that can investigate areas that have larger trust uncertainty.

Outside of academics, Chris is an avid long distance runner and T.V./Movie connoisseur. 

Lunch and drinks provided courtesy of the Institute for Materials (IMAT)

Time:              11am-12pm             
Place:              Klaus 1116 West           

Speaker:         Peter Griffiths, First-year FLAMEL trainee

Title:

“Exploring Process-Structure-Property Linkages for Slot Die Extruded Filtration Membranes”
Abstract:

Slot die extrusion is a manufacturing process for thin films that offers several benefits over other methods (such as doctor blade or spin coating) in process control and scalability while allowing for continuous processing. Much of the research of this process has been directed at how combinations of process parameters result in defects in the film. But how is the final membrane structure affected by processing parameters during defect free casting? Is it possible to tune the process to improve the final film/membrane properties/performance?

This talk will discuss the preliminary investigations into how to apply to the Materials Knowledge System framework to finding process-structure-property linkages in cellulose acetate filtration membranes produced using slot die extrusion and analyzed using micro computed tomography.

Bio:

Peter Griffiths is a second year PhD student in the School of Mechanical Engineering working for Dr. Tequila Harris in the Polymer Thin Films Processing Group studying thin film manufacturing. He is particularly interested in computational modeling of nano-composite solutions that exhibit viscoelastic flow behavior to better understand structure-process-function relationships. His goal is to develop computational tools to model the process physics to tailor particle distributions and material properties during thin film manufacture, for varying applications.

Peter previously attended the University of Florida where he earned a B.S. in Mechanical Engineering and a B.S. in Aerospace Engineering in 2006. During his undergraduate studies, he interned for the Aviation Division of General Electric, which led to a position in the Edison Engineering Development Program upon graduation. He returned to school full-time to earn a M.S. in Mechanical Engineering from the University of South Florida in 2013, studying the force and wetting phenomenon involved in using droplets to transport wafers. Peter’s current interests outside of his academic pursuits includes running, racquetball, team sports, cooking, and history. 

*Our next Chalk-Talk is scheduled for Thursday, April 7, with discussions led by first year FLAMEL trainee Chris Shartrand.  For a list of this semester’s upcoming talks, please visit http://flamel.gatech.edu/newsroom

Every year, security experts see new evolutions in cyberthreats to people, businesses and governments. Our adversaries know no boundaries. Cybersecurity is everyone's business.

The annual Summit features breakfast, lunch, keynote speeches, panel discussions, and more. All attendees at this full-day summit receive a copy of the 2017 Cyber Threats, Trends & Technologies Report.

Registration is closed.

Morning

9:30 a.m.
Keynote by Keynote by Annie Antón, chair, School of Interactive Computing; director, ThePrivacyPlace.org

10:00 a.m.
Meet the Students / Fall '16 Demo Day

11:00 a.m. - Noon
Panel: “Partners in Crisis? Legislation has yet to improve information sharing”
Evan Glover, senior counsel, GE Transportation
Paul Huesken, chief information assurance officer, Coca-Cola
Lee Kirschbaum, special agent, FBI
Jimmy Lummis, associate director, Georgia Tech Cyber Security

Afternoon

1:30 p.m.
Keynote by Tom Fanning, chairman, president & CEO, Southern Company

Breakout Sessions

2:30 - 3:30 p.m.
TRACK A: “Ransomware: How to respond”
Chris Smoak, division chief, Cyber Technology & Information Security Lab, GTRI
Evan Downing, Ph.D. student, Georgia Tech

TRACK B: “The Cyber Policy Landscape at Home & Abroad”
Klaus Brisch, partner, DWF Germany
Rick Stewart, director of cyber security services, CGI Federal of Canada
Peter Swire, associate director of policy, Institute for Information Security & Privacy

3:30 - 4:30 p.m.
TRACK A: “Cryptocurrency: Current and future state of dark money”
Mark Ray, PwC, director, Cyber Investigations and Breach Response
SSA Chad Hunt, FBI Atlanta – Computer Intrusion Squad
Michael Farrell, chief research scientist, CTISL – GTRI

TRACK B: “Cybersecurity: Not just the IT department’s problem”
COL Alprentice Smith, Joint Functional Component Command Headquarters, U.S. Army Cyber Command
Leo Mark, associate dean, Georgia Tech Professional Education
Taesoo Kim, assistant professor, School of Computer Science

The ASM-GT Materials Data Challenge is a community-building 2-day event, which focuses on the emerging discipline of materials informatics.  The challenge includes a juried competition, inviting students in computer science, data science and materials science, as well ass opportunities for professional networking with representatives from academia, professional societies and industry.  Both individual and team participation are allowed (maximum team size is 4 people).  Prizes include $500 main prize and ASM Certificates in varous categories.  All participants will receive GT-branded T-shirts as a token of appreciation for participation in this event from Georgia Tech.  Food, fun and new contacts are also included!

Challenge Problem

Please visit this site later for updates on the Challenge Problem

Event Timing:

April 8, 9:00am - April 9, 6:00pm

Event Address:

Pettit Building (Microelectronics Research Center), Room 102

791 Atlantic Ave, Atlanta, GA 30332

Registration:

https://docs.google.com/forms/d/1CTQUUyZsiyF1EKYaNymVQbs0cTo_juUnboxmuY4...

Our relationship with personal technology and how we use it is evolving. Research through our interdisciplinary teams shows the opportunities that exist for technology to address long-standing societal challenges and how we can make new connections to advance our lives and those of others.

The GVU Center Research Showcase will offer:

- Hands-on and interactive demonstrations to experience technology in a wide variety of formats.

- Research from more than 30 labs with specialties that cover broad areas such as mobile and wearable technology, digital media, transportation, online communities, artificial intelligence, game development, graphics, user interfaces and much more.

- Networking with industry representatives and access to researchers and their latest work.

- A range of innovative ideas, interfaces and devices that can only be experienced here.

What will shape your technology experience in the future? Come find out October 26, 2-5 p.m., in the Technology Square Research Building on the Georgia Tech campus.

Our Relationship with Technology is Evolving - -

See Where the Ideas Begin

A key signing party is a gathering where individuals verify and sign each other’s encryption keys, which is essential to read and receive encrypted email. If you don’t have an encryption key and/or would like to learn about GPG/PGP methods for protecting your data, attend the “Introduction to GPG” at 9 a.m. in Rich 242. (Feel free to skip this part if you are already a GPG pro!) At 10 a.m. in Rich 242, we will start the actual key signing. This process takes less than one hour, and gives you the assurance that the message you intend to send is the message that arrives intact.

Please remember to bring:

• Your GPG fingerprint
• Your photo ID

If you do not have a GPG fingerprint, arrive at 9 a.m. and we will help you secure one.

Coffee and donuts will be provided!

To learn more, visit: https://security.gatech.edu/pgpbasics

9:00am - 9:05am  Wecome (Richard Fujimoto)

9:05am - 9:15am  IMAT Overview (David McDowell)

9:15am - 9:45am  FLAMEL Program Overview (Richard Fujimoto)

9:45am - 10:15am  Materials Informatics Course (Surya Kalidindi)

10:15am - 10:30am  Break (All)

10:30am - 11:00am  Entrepreneurship Programs (Terry Blum)

11:00am - 11:30am Assessment Report and program revisions (Joshep McCrary, Richard Fujimoto)

11:30am - 12:15pm  Student Poster Session (FLAMEL Trainees & Associate)

12:15pm - 1:00pm  Lunch (All)

1:00pm - 2:00pm  Faculty Roundtable (Faculty Advisors)

2:00pm - 4:00pm  Private Board Meeting (Advisory Board)

4:00pm - 4:30pm  Debrief (Advisory Board and Faculty)

Please RSVP to Holly Rush, FLAMEL Program Manager, if you plan to attend the advisory board meeting.  

Agenda

8:30–9:00        Continental Breakfast and Introductions

9:00–9:30        FLAMEL Overview, Richard Fujimoto

9:30–10:00      Materials Informatics Course and MATIN, Surya Kalidindi

10:00–10:30    Entrepreneurship Programs, Lalita Kaligatla

10:30–11:00    Assessment report and program revisions, Joseph McCrary (WestEd) and Richard Fujimoto

11:00–11:15    Break

11:15–12:00    Student panel session and poster session (student research, class projects, Q&A), FLAMEL trainees and associates

12:00–1:00      Lunch

1:00–2:00        Faculty Roundtable (introductions, research interests, Q&A), Faculty Advisors

2:00–4:00        Private Board Meeting (discussions and writing report)

4:00–4:30        Debrief (feedback, suggested revisions, plans for future board meetings), Advisory Board and Faculty

Nobel Laureate Lecture: Michael Levitt

The development of multiscale models for complex chemical systems began in 1967 with publications by Warshel and Levitt, recently recognized by the 2013 Nobel Committee for Chemistry.  The simplifications used then at the dawn of the age of computational structural biology were mandated by computers that were almost a billion times less cost-effective than those we use today. These same multiscale models have become increasingly popular in applications that range from simulation of atomic protein motion, to protein folding and explanation of enzyme catalysis. 

In this talk, Michael Levitt will describe the origins of computational structural biology and show some of the most exciting current and future applications

Biography:

Born in South Africa 1947, Michael Levitt visited London at the age of 16 to be profoundly influenced by John Kendrew's 1944 BBC TV series "The Thread of Life".  After receiving a BSc in Physics at King’s College London and spending a year with Prof. Shneior Lifson and his PhD student Arieh Warshel at the Weizmann Institute in Israel, Levitt joined the Laboratory of Molecular (LMB), Cambridge, in 1968 .  His PhD thesis on Protein Conformation Analysis described use of classical force-fields and introduced energy refinement.

Levitt went back to Israel as an EMBO postdoc with Lifson. His then collaboration with Warshel resulted in new multi-scale approaches to molecular modeling: coarse-grained models that merge atoms to allow folding simulation and hybrid models that combine classical and quantum mechanics to explain how enzymes works by electrostatic strain.  In 1974, Levitt returned to LMB for three years, spent two years with Francis Crick at Salk and seven years at Weizmann, before moving to Structural Biology at Stanford from 1987.

His diverse interests have included RNA & DNA modeling, protein folding simulation, classification of protein folds & protein geometry, antibody modeling, x-ray refinement, antibody humanization, side-chain geometry, torsional normal mode, molecular dynamics in solution, secondary structure prediction, aromatic hydrogen bonds, structure databases, and mass spectrometry.  Levitt’s current postdocs work on protein evolution, the crystallographic phase problem and Cryo-EM refinement.

While enjoying membership of the Royal Society and the National Academy, Levitt remains an active programmer, a craft skill of which he is particularly proud.  His post-prize ambitions are two fold and likely inconsistent:  (1) Work single-mindedly as he did in the mid-1970’s on hard problems and (2) help today’s young scientists gain the recognition and independence that Levitt’s generation enjoyed.

Married in 1968 to Rina, an active artist, they have three children and a rapidly increasing number of grandchildren, all of whom help Levitt stay more-or-less normal.

In November of 2014, SC is going back to New Orleans with new ideas and a fresh take on HPC. Spotlighting the most original and fascinating scientific and technical applications from around the world, SC14 will once again bring together the HPC community—an unprecedented array of scientists, engineers, researchers, educators, students, programmers, system administrators, and developers—for an exceptional program of technical papers, tutorials, timely research posters, and Birds-of-a-Feather (BOF) sessions.

The SC14 Exhibition Hall will feature exhibits of the latest and greatest technologies from industry, academia, and government research organizations; many of these technologies will be seen for the first time in New Orleans. Mark your calendar and make your way to New Orleans. No city offers the same extraordinary mix of food, music, culture, and history; and no conference offers a better opportunity to view why HPC matters.

Join the community in November to share our collective accomplishments and to engage in important conversations of how we make HPC Matter to our lives, our future, our communities, and our world.

This event replaces the original workshop scheduled for January 31, which was postponed due to inclement weather. If you were registered for the original event, please resubmit your registration so that we may maintain an accurate attendee list. Also, new registrants are welcome.

Register Now

Overview 

The Georgia Tech Computational Sustainability Workshop brings together researchers with interests at the intersection of computing and sustainability to explore computation as an enabler for creating more sustainable, resilient cities.

The event will offer participants the opportunity to develop unifying research themes, which can be used to create large-scale research projects and research thrusts in the computational sustainability area.

Agenda

1:00     Introductions and Overview
            Richard Fujimoto and John Crittenden

Research Presentations

1:20     Bert Bras, Mechanical Engineering
            Computations in Sustainable Design & Manufacturing

1:32     Ashok Goel, Interactive Computing
            Computational Biomimicry

1:44     Kishore Ramachandran, Computer Science
            System Support for Internet of Things

1:56     David Bader, Computational Science & Engineering
            Massive Scale Data Analytics

2:08     Bistra Dilkina, Computational Science & Engineering
            Discrete Optimization for Biodiversity Conservation and Beyond

2:20     Discussion

2:35     Break

Research Presentations

2:45     Michael Hunter, Civil & Environmental Engineering
            Intelligent Mobility

2:57     Marilyn Smith & John-Paul Clarke, Aerospace Engineering
            A Systems Approach to Designing Sustainable Energy-Based Communities in Developing Countries

3:09     Godfried Augenbroe, Architecture
            Computational Models of New and Existing Buildings

3:21     Subhro Guhathakurta, City and Regional Planning
            Application of Geospatial Technologies for Enhancing Urban Mobility, Community Health, and Quality of Life

3:33     Polo Chau, Computational Science & Engineering
            Smart Grid Meets Big Data

3:45     Discussion

4:00     Breakout Groups

5:00     Breakout Reports and Networking Reception

6:00     Adjourn

Title:

Understanding the effect of social media:

Abstract:

With the emergence of social media and Web 2.0, broadcasting in the online environment has evolved into a new form of marketing due to the much broader reach enabled by information technology. This paper quantifies the effect of artists’ different broadcasting activities on a leading social media site for music, MySpace, on music sales. We employ a panel vector auto-regression (PVAR) model to investigate the inter-relationship between broadcasting promotions in social media and music sales, while controlling for influential factors such as album prices, advertising in traditional media channels, artist popularity, and the impact of user-generated content. We characterize two types of broadcast messages under the MySpace context, personal and automated. We find that broadcasting in social media has a significant effect on sales even after controlling for the aforementioned factors, and more importantly the effect mainly comes from personal messages rather than automated messages. Our findings also point to the importance of conducting captivating conversations with customers in the organizational use of social media.

Bio: 

Yu (Jeffrey) Hu is an associate professor at Scheller College of Business, Georgia Institute of Technology. He received his Ph.D. from MIT’s Sloan School of Management. His research studies electronic commerce, mobile commerce, Internet retailing, social media, and online advertising. He has consulted for many retailing and publishing companies and European Commission. His research has been published in top journals such as Management Science, Information Systems Research, and Sloan Management Review, and has been discussed extensively and cited by many media outlets such as New York Times and National Public Radio. He is an associate editor for Management Science and Information Systems Research.

All Georgia Tech researchers and faculty members interested in participating in the FLAMEL program are encouraged to attend the workshop, which includes an opportunity to initiate the formation of multidisciplinary faculty teams.

Space is limited to facilitate dialogue, so please RSVP early by completing a brief registration form.

The tentative agenda includes the following components:

1:00 Introductions/Welcome

1:15 Materials Genome Initiative

1:45 FLAMEL Overview

2:15 Break

2:30 Tutorial: Big Data Research Themes and Examples

• Overview of Big Data Areas
• Materials Science
• Data/Computation
• Software/Platform Demo
• Identifying Data Analysis/Computational Problems for FLAMEL Projects

4:00 "Speed Dating"/Reception (opportunity for researchers to identify potential new collaboration opportunities)

5:00 Adjourn

The workshop will be held at the Georgia Tech Hotel in Conference Room A, followed by the "Speed Dating" session and reception in Salons 4-6. 

Abstract:
While Python has been a popular and powerful language for scientific computing for a while now, its future in the broader data analytics realm is less clear, especially as market forces and technological innovation are rapidly transforming the field.

In this talk, Peter will introduce some new perspectives on "Big Data" and the evolution of programming languages, and present his thesis that Python has a central role to play in the future of not just scientific computing, but in analytics and even computing in general. As part of the discussion, many new libraries, tools, and technologies will be discussed (both Python and non-Python), both to understand why they exist and where they are driving technical evolution.

Bio:
Peter holds a B.A. in Physics from Cornell University and has been developing applications professionally using Python since 2001. Before co-founding Continuum Analytics in 2011, Peter spent seven years at Enthought designing and developing applications for a variety of companies, including investment bankers, high-frequency trading firms, oil companies, and others. In 2007, Peter was named Director of Technical Architecture and served as client liaison on high-profile projects. Peter also developed Chaco, an open-source, Python-based toolkit for interactive data visualization.  Peter's roles at Continuum Analytics include product design and development, software management, business strategy, and training.

Title: 

Galerkin Methods for Monotone Linear Complementarity Problems

Abstract:
Linear complementarity problems are one way to encode the first-order optimality conditions for inequality-constrained optimization or saddle-point problems.  So, LCPs arise in a wide variety of areas, including machine learning, planning, game theory, and physical simulation.  In all of these areas, to handle large-scale LCP instances, we need fast approximate solution methods.  One promising idea is Galerkin approximation, in which we search for the best answer within the span of a given set of basis functions.  For equality-constrained problems, Galerkin methods have had a long history of practical and theoretical successes.  Unfortunately, the most straightforward way to apply Galerkin approximation to LCPs leads to difficulties in practice, including worse approximation errors than might be expected based on the ability of the basis to represent the desired solution.  So, in this talk, I'll present a new Galerkin method for LCPs that attempts to address the above difficulties.

Bio:

Dr. Gordon is an Associate Research Professor in the Department of Machine Learning at Carnegie Mellon University, and co-director of the Department's Ph. D. program. He works on multi-robot systems, statistical machine learning, game theory, and planning in probabilistic, adversarial, and general-sum domains.  His previous appointments include Visiting Professor at the Stanford Computer Science Department and Principal Scientist at Burning Glass Technologies in San Diego.  Dr.  Gordon received his B.A. in Computer Science from Cornell University in 1991, and his Ph.D. in Computer Science from Carnegie Mellon University in 1999.

May 13, 2013     8:45 am - 8:00 pm

May 14, 2013      8:30 am - 5:15 pm

Location: Technology Square Research Building (TSRB),   www.trsb.gatech.edu

The meeting is open to anyone who is interested in contributing to, and participating in the OpenCL community. IWOCL is the premier forum for the presentation and discussion of new designs, trends, algorithms, programming models, software, tools and ideas for OpenCL. Additionally, IWOCL provides a formal channel for community feedback to OpenCL promoters and contributors.

Visit the website for more information regarding registration, program, etc.

http://iwocl.org/registration/1st-international-workshop-on-opencl/

A Joint Seminar from the Center for Signal and Information Processing and Institute for Data and High Peformance Computing

Speaker: 

Aaron Clauset from University of Colorado Boulder

Abstract:

Networks have become a powerful tool for studying complex systems: they provide an abstraction of a system's interacting parts that is both general enough to encompass important features of real systems and simple enough to offer clear insights and general results. Already, networks are a central tool in understanding a wide range of biological, social, and technological phenomena.

Until recently, most work in network science focused on simple statistical measures, such as degree distributions and correlations, centrality measures, etc. These have yielded great insight but they capture only a fraction of the complexity of real-world networks. Increasingly, progress on important questions about the structure, function and dynamics of networks depends on going beyond these measures to identify and understand large-scale structural patterns, like modules and hierarchies, and to leverage vertex and edge annotations. Generative models and scalable inference algorithms provide a powerful, statistically principled and data-driven approach to solving these problems.

In this talk, I'll describe my recent work on generative models of modular and hierarchical organization in complex networks. Such organizational patterns, it turns out, can simultaneously explain many of the statistical regularities most commonly studied in networks, can generalize a single network to an ensemble of statistically similar networks, and can make accurate predictions about missing links. Importantly, these models can be extended to include arbitrary degree distributions, edge weights, latent spaces and network dynamics, which opens many new questions for analysis.

Biographical sketch:

Aaron Clauset is an Assistant Professor in the Department of Computer Science and the BioFrontiers Institute at the University of Colorado Boulder, where he is affiliated faculty in the Department of Ecology and Evolutionary Biology and the Department of Applied Mathematics. He is also External Faculty at the Santa Fe Institute. He received a PhD in Computer Science, with distinction, from the University of New Mexico, a BS in Physics, with honors, from Haverford College, and was an Omidyar Fellow at the prestigious Santa Fe Institute.

He is an internationally recognized expert on network science and computational analyses of complex systems. His work has appeared in prestigious scientific venues like Nature, Science, JACM, AAAI, ICML, STOC, SIAM Review, and Physical Review Letters, and has been covered in the popular press by the Wall Street Journal, The Economist, Discover Magazine, New Scientist, Wired, Miller-McCune, the Boston Globe and The Guardian.

Speaker: Dr. Yousef Saad, College of Science & Engineering Distinguished Professor in the Department of Computer Science & Engineering at the University of Minnesota

Title:

Multilevel Algebraic Preconditioning Techniques with Applications

 Abstract:

Solving linear systems of equations with iterative methods is becoming more difficult due to a number of new challenges. Matrices of these systems are becoming larger, more ill-conditioned, and are often poorly structured, and indefinite. Multilevel methods have been advocated for handling some of these challenges. This talk will introduce a variety of multilevel preconditioners for solving linear systems of equations, with an emphasis on indefinite systems. We begin with the Algebraic Recursive Multilevel Solver (ARMS) and see how a class of "coarsening" schemes can be adapted to this framework. 

ILU-type preconditioners have difficulties for some types of indefinite problems. We will show how they can be adapted for problems arising from Helmholtz equations. Then a new class of methods based on low-rank approximations which has some appealing features will be introduced. The methods handle indefiniteness quite well and are more amenable to SIMD computations, which makes them attractive for GPUs.  We will then present an application in dynamic mean field theory (DMFT) where the problem is to compute the diagonal of the inverse of a matrix.

 Bio:

Yousef Saad is a College of Science & Engineering Distinguished Professor in the Department of Computer Science & Engineering at the University of Minnesota.  He holds the William Norris Chair for Large-Scale Computing and is a fellow of SIAM and AAAS.  He is known for his contributions to matrix computations, including iterative methods for solving large sparse linear algebraic systems, eigenvalue problems, and parallel computing.  Dr. Saad is an ISI highly cited researcher in mathematics and is the author of the highly cited book, Iterative Methods for Sparse Linear Systems.  For more information, please visit http://www-users.cs.umn.edu/~saad

Register here: Registration Page

Location: Marcus Nanotechnology Research Building (Rooms 1116-1118), 345 Ferst Drive, Atlanta, Ga 30332

Program Format

The workshop will consist of several invited talks, a panel, and a poster session. 

Workshop Schedule

8:30 - 8:50   Breakfast

8:50 – 9:00   Welcoming Remarks - Richard Fujimoto (Director of the Institute for Data and High Performance Computing), Haesun Park (Director of the Center for Data Analytics), Zvi Galil (Dean of the College of Computing)

9:00 – 10:30   Invited Talks, Session Chair: Nina Balcan

9:00 – 9:15   Computational Challenges in the Development of Improved Cancer Diagnostics and Therapies - John McDonald (Georgia Tech, Biology)

9:15 – 9:30   Applied Data Analytics at GTRI - Dan Campbell (Georgia Tech Research Institute)

9:30 – 9:45   Data and Computational Challenges in Integrative Biomedical Informatics - Joel Saltz (Director of the Center for Comprehensive Informatics; Emory University, Biomedical Informatics)

9:45 – 10:00   Sparsity and Rank Constraints in Solving Underdetermined Systems - Justin Romberg (Georgia Tech, Electrical and Computer Engineering)

10:00 – 10:15   Data Analytics for Materials Datasets - Surya Kalidindi (Georgia Tech, Mechanical Engineering)

10:15 – 10:30   Leveraging Geospatial Technologies in Planning for a Sustainable Future - 

Subhro Guhathakurta (Director of the Center for Geographic Information Systems; Georgia Tech, Architecture)

10:30 – 10:45   Break

10:45 – 12:10   Invited Talks, Session Chair: Hongyuan Zha

10:45 – 11:00   Operational Aspects of Big Data for a Research University - Ron Hutchins (Georgia Tech, Office of Information Technology)

11:00 – 11:15   The Role of Predictive Models in Data Analytics - Xiaoming Huo (Georgia Tech, Industrial and Systems Engineering)

11:15 – 11:30   The Challenge of Large Data Sets – Examples from Petascale Simulations of Fluid Turbulence - P.K. Yeung (Georgia Tech, Aerospace Engineering)

11:30 – 11:45   Big Data Analytics: Long Tail, Web Analytics, and Social Media - Jeffrey Hu (Georgia Tech, Business)

11:45 – 12:00   Learning and Optimizing Information Diffusion - Le Song (Georgia Tech, Computational Science and Engineering)

12:00 – 12:10   Remarks about Data Analytics at Georgia Tech - Steve Cross (Georgia Tech, Executive VP of Research)

12:10 – 1:45   Lunch and Poster Session

1:45 – 2:45   Panel Discussion - Panelists: Jianjun Shi (Industrial Systems & Engineering), John Wise (Physics), Suresh Menon (Aerospace Engineering), Mark Braunstein (Associate Director of the Health Systems Institute; Interactive Computing), John Stasko (Interactive Computing)

Chair: Polo Chau (Georgia Tech, Computational Science and Engineering)

2:45 – 2:50   Concluding Remarks - Haesun Park and Richard Fujimoto

List of Posters

A Cubic Algorithm for Computing Gaussian Volume
Authors: Ben Cousins and Santosh Vempala

Accelerating Analysis and Data Reduction in Experimental Combustion Research through High Performance Computing
Authors: Benjamin Wilde, Christopher Foley, Andrew Marshall, Benjamin Emerson, J. Matt Quinlan, Tim Lieuwen, Drew Bratcher and Matthew Wolf

 Apolo: Interactive Graph Exploration Combining Machine Learning and Visualization
Authors: Polo Chau, Niki Kittur, Jason Hong and Christos Faloutsos

Beyond Sentiment: The Manifold of Human Emotions
Authors: Seungyeon Kim, Fuxin Li, Guy Lebanon and Irfan Essa

Bounded Low Rank Matrix Approximation
Authors: Ramakrishnan Kannan, Mariya Ishteva and Haesun Park

Distributed Clustering on Graphs
Authors: Maria-Florina Balcan, Steven Ehrlich and Yingyu Liang

Distributed Non-negative Matrix Factorization
Authors: Long Tran, Hua Ouyang, Alexander Gray and Haesun Park

Efficient Active and Semi-Supervised Learning of Disjunctions
Authors: Maria Florina Balcan, Chris Berlind, Steven Ehrlich and Yingyu Liang

Fast Rank-2 Non-negative Matrix Factorization for Hierarchical Clustering
Authors: Da Kuang and Haesun Park

Infrastructure for Managing and Analyzing Biological Networks Derived 
from Collections of Plant Images
Authors: Abhiram Das, Alexander Bucksch and Joshua S. Weitz

Intelligent Systems and Big Data at GTRI
Authors: Elizabeth Whitaker and Ethan Trewhitt

Local Low-Rank Matrix Approximation
Authors: Joonseok Lee, Seungyeon Kim, Guy Lebanon and Yoram Singer

Low Rank Estimation of Smooth Kernels on Graphs
Authors: Vladimir Koltchinskii and Pedro Rangel

OPAvion: Mining & Visualization in Large Graphs
Authors: Polo Chau, Leman Akoglu, U. Kang, Danai Koutra and Christos Faloutsos

Potential Induced Random Teleportation on Finite Graphs
Authors: Shui-Nee Chow, Xiaojing Ye and Haemin Zhou

Red Fox: An Execution Environment for Data Warehousing Applications on GPUs
Authors: Haicheng Wu, Gregory Diamos, Tim Sheared, Molham Aref and Sudhakar Yalamanchili

StochasticADMM for Nonsmooth Optimization
Authors: Hua Ouyang, Niao he, Long Tran and Alexander Gray

The Sample Complexity of Independent Component Analysis
Authors: Santosh Vempala and Ying Xiao

Uncover Topic-Sensitive Information Diffusion Networks
Authors: Nan Du, Le Song, Hyenkyun Woo and Hongyuan Zha

VisIRR: Interactive Visual Information Retrieval and Recommendation for Large-scale Document Data
Authors: Jaegul Choo, Changhyun Lee, Edward Clarkson, Zhicheng Liu, Hanseung Lee, Duen Horng (Polo) Chau, Fuxin Li, Ramakrishnan Kannan, Charles D. Stolper, David Inouye, Nishant Mehta, Hua Ouyang, Subhojit Som, Alexander Gray, John Stasko and Haesun Park

Title:

Modeling Cardiovascular Flow Dynamics

Abstract:

Accurate and reliable modeling of cardiovascular hemodynamics has the potential to improve understanding of the localization and progression of heart diseases. However, building a detailed, realistic model of human blood flow is a formidable mathematical and computational challenge. The simulation must combine the motion of the fluid, the intricate geometry of the blood vessels, continual changes in flow and pressure driven by the heartbeat, and the behavior of suspended bodies such as red blood cells. Such simulations can provide insight into factors like endothelial shear stress that act as triggers for the complex biomechanical events that can lead to atherosclerotic pathologies. Currently, it

is not possible to measure endothelial shear stress in vivo, making these simulations a crucial component to understanding and potentially predicting the progression of cardiovascular disease. In this talk, I will present and examine our approach for enabling an efficient parallel model of the fluid  on both the IBM Blue Gene/P and Blue Gene/Q architectures and discuss the use of parallel-in-time decomposition to extend the number of time steps that can be modeled in a given wall-clock time.

Bio:

Amanda Peters Randles is a Ph.D. candidate in Applied Physics at Harvard University under the supervision of Efthimios Kaxiras and Hanspeter Pfister. She is interested in the design of large-scale parallel applications targeting problems in physics.  Her thesis research is focused on the development and deployment of a general purpose, multiscale methodology to study blood flow patterns in complex environments relating to real patient arterial geometries.  She received her Bachelor's Degree in both Computer Science and Physics from Duke University, and her Master's Degree in Computer Science from Harvard University.  Prior to graduate school, she worked for three years as a software developer at IBM on the Blue Gene Development Team. For more information please visit: people.seas.harvard.edu/~apeters

Title:

Optimization in Learning and Data Analysis

Abstract:
Optimization tools are vital to data analysis and learning. The optimization perspective has provided valuable insights, and optimization formulations have led to practical algorithms with good theoretical properties. In turn, the rich collection of problems in
learning and data analysis is providing fresh perspectives on optimization algorithms and is driving new fundamental research in the area. After a brief survey, we focus on several problems --- signal reconstruction, manifold learning, and regression/classification ---
describing in each case recent research in which optimization algorithms have been developed and applied successfully.

Bio:

• Professor in the Computer Sciences Department and Industrial and Systems Engineering at UW-Madison
• Investigator in the Optimization Theme in the Wisconsin Institute for Discovery at UW-Madison.
• Past Chair and current Vice Chair of the Mathematical Optimization Society (formerly Mathematical Programming Society).
• SIAM Fellow and Member of the Board of Trustees of SIAM.
• Member of the Science Advisory Board of IPAM.

http://www.cs.wisc.edu/users/swright

Speaker: Sharon Aviran, Center for Computational Biology at UC Berkeley

Date: Tuesday, February 26, 2013

Location:  Klaus 1456

Time: 11:00am-12:00pm

-----------------------------------

Title:

Modeling and High-Throughput Analysis of RNA Structure Mapping Experiments 

Abstract:

New regulatory roles continue to emerge for both natural and engineered RNAs, many of which have specific structures essential to their function. This highlights a growing need to develop technologies that enable rapid and accurate characterization of RNA structure. Yet, available techniques that are reliable are also vastly limited, while the accuracy of popular computational methods is generally poor. These limitations thus pose a major barrier to comprehensive determination of structure from sequence.

To address this need, we have developed a high-throughput structure characterization assay, called SHAPE-Seq, which simultaneously measures structural information at nucleotide-resolution for hundreds of distinct RNAs. SHAPE-Seq combines a novel chemistry with next-generation sequencing of its products. Following sequencing, we extract the structural information using a fully automated algorithmic pipeline that we developed. In this talk, I will focus on SHAPE-Seq's analysis methodology, which relies on a novel probabilistic model of a SHAPE-Seq experiment, adjoined by maximum-likelihood parameter estimation. I will demonstrate the accuracy, simplicity, and efficiency of our approach, and will then present an algorithm that uses such structure mapping data to inform computational RNA secondary structure prediction.

Bio

Sharon Aviran is a postdoctoral researcher at the Center for Computational Biology at UC Berkeley, working with Prof. Lior Pachter. Her current research interests are in the areas of Genomics and Functional Genomics, focusing on developing computational methods for high-throughput analysis of RNA molecular dynamics. She pursued her PhD in Electrical Engineering at UCSD, working with Professors Paul Siegel and Jack Wolf, and specialized in signal processing for communications and in information theory. She was awarded the 2006 Sheldon Schultz Prize for Excellence in Graduate Research, and was a Calit2 Fellow at UCSD and a Postdoctoral Innovation Fellow at UC Berkeley. In 2012, she received the NIH K99/R00 career development award for her research on RNA structural dynamics.

-----------------------------------

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Title:

Challenges in Computational Sustainability

Abstract:

Computational sustainability is a new interdisciplinary research focused on computational problems that arise in the quest for sustainable development.  The goal of sustainable development, a notion introduced in 1987 by the seminal report of the United Nations World Commission on Environment and Development, is to balance environmental, economic, and societal factors to “meet the needs of the present without compromising the ability of future generations to meet their own needs.” In this talk, I will provide a sample of computational sustainability problems, from the areas of wildlife conservation, biodiversity, poverty mitigation, climate and environment monitoring. I will describe, for example, network design problems motivated by challenging planning problems in wildlife conservation. In this context, I will present a network design optimization framework for stochastic diffusion processes, such as species dispersal, fire spread, information propagation, and disease outbreak. I will also emphasize  the unique opportunities for computing and information scientists to contribute to the new research area of computational sustainability and show how the challenges in this area call for an integration of work from different areas in computer science, such as constraint reasoning, optimization, algorithm design, machine learning, citizen science, and human computation.

Bio:

Bistra Dilkina is a postdoctoral researcher at the Institute for Computational Sustainability. She received a Ph.D. in computer science from Cornell University in 2012. Her research interests lie at the intersection of artificial intelligence and operations research, and machine learning, with a focus on advancing the state of the art in combinatorial optimization techniques for solving real-world large-scale problems, particularly ones that arise in sustainability areas such as conservation planning. Her work spans constraint reasoning and optimization, network design, stochastic optimization, machine learning, and game theory.

Title:

Cyber Games

Abstract:

Over the last few years I have been working on game theoretic models of security, with a particular emphasis on issues salient in cyber security. In this talk I will give an overview of some of this work. I will first spend some time motivating game theoretic treatment of problems relating to cyber and describe some important modeling considerations. In the remainder, I will describe two game theoretic models (one very briefly), and associated solution techniques and analyses. The first is the "optimal attack plan interdiction" problem. In this model, we view a threat formally as a sophisticated planning agent, aiming to achieve a set of goals given some specific initial capabilities and considering a space of possible "attack actions/vectors" that may (or may not) be used towards the desired ends. The defender's goal in this setting is to "interdict" a select subset of attack vectors by optimally choosing among miti-gation options, in order to prevent the attacker from being able to achieve its goals. I will describe the formal model, explain why it is challenging, and present highly scalable decomposition-based integer programming techniques that leverage extensive research into heuristic formal planning in AI. The second model addresses the problem that defense decisions are typically decentralized. I describe a model to study the impact of decentralization, and show that there is a "sweet spot": for an intermediate number of decision makers, the joint decision is nearly socially optimal, and has the additional benefit of being robust to the changes in the environment.

Finally, I will describe the Secure Design Competition (FIREAXE) that involved two teams of interns during the summer of 2012. The problem that the teams were tasked with was to design a highly stylized version of an electronic voting system. The catch was that after the design phase, each team would attempt to "attack" the other's design. I will describe some salient aspects of the specification, as well as the outcome of this competition and lessons that we (the designers and the students) learned in the process.

 Bio:

Yevgeniy Vorobeychik is a Principal Member of Technical Staff at Sandia National Laboratories. Between 2008 and 2010 he was a post-doctoral research associate at the University of Pennsylvania Computer and Information Science department. He received Ph.D. (2008) and M.S.E. (2004) degrees in Computer Science and Engineering from the University of Michigan, and a B.S. degree in Computer Engineering from Northwestern University. His work focuses on game theoretic modeling of security, algorithmic and behavioral game theory and incentive design, optimization, complex systems, epidemic control, network economics, and machine learning. Dr. Vorobeychik has published over 50 research articles on these topics, including publications in top Computer Science, Operations Research, Business, and Physics journals and conferences. Dr. Vorobeychik was nominated for the 2008 ACM Doctoral Dissertation Award and received honorable mention for the 2008 IFAAMAS Distinguished Dissertation Award. In 2012 he was nominated for the Sandia Employee Recognition Award for Technical Excellence. He was also a recipient of a NSF IGERT interdisciplinary research fellowship at the University of Michigan, as well as a distinguished Computer Engineering undergraduate award at Northwestern University.

Speaker: Josh Patterson, Cloudera

Title:

Knitting Boar

Abstract:

Online learning techniques, such as Stochastic Gradient Descent (SGD), are powerful when applied to risk minimization and convex games on large problems. However, their sequential design prevents them from taking advantage of newer distributed frameworks such as Hadoop/YARN. In this session, we will introduce “Knitting Boar”, an open-source Java library for performing distributed online learning on a Hadoop cluster under YARN. We will give an overview of how Knitting Boar works and examine the lessons learned from YARN application construction.

Bio:

Josh Patterson is a Principal Solution Architect at Cloudera. Prior to joining Cloudera, he was responsible for bringing Hadoop into the smartgrid during his involvement in the openPDC project. His focus in the smartgrid realm with Hadoop and HBase was using machine learning to discover and index anomalies in time series data. Josh is a graduate of the University of Tennessee at Chattanooga with a Bachelors in Business Management and a Masters of Computer Science with a thesis titled "TinyTermite: A Secure Routing Algorithm" where he worked in mesh networks and social insect swarm algorithms. Josh has over 15 years in software development and continues to contribute to projects such as Apache Mahout, openPDC, and JMotif in the open source community. Currently Josh focuses on open source parallel linear modeling and optimization techniques.

Abstract:

We give an overview of the IntelliScience approach to data and image analysis using a comparative algorithmic methodology in feature classification, change detection and anomaly identification and the challenges for performance. 

Bio: 

Bryan Donaldson joined IntelliScience in 2004 after 21 years of application and system development work on real-time systems and distributed client-server applications and I18N and G11N for global products. At IntelliScience, Mr. Donaldson currently serves as the team leader for development and one of the lead designers of the IntelliScience data analysis algorithms and systems.